The purpose of this study is to investigate the roadside agricultural product shops located in Miryang city, and to find out the current situation on how people rate the importance and satisfaction levels of various aspects through surveys on sellers and consumers. With this information, the main problems and possible solutions are analyzed with the Important Performance Analysis(IPA) method. First, building parking spaces for customers should be prioritized to improve safety. Because many roadside shops for agricultural products are located alongside two-lane roads, sufficient parking spaces are needed for the consumers' safety. Second, to enhance the rural landscape, consumers express that improving store quality and integrating more with the environment are important. Store owners should take more care in maintaining store quality so that customers do not experience inconvenience while shopping. Futhermore, institutional guidelines and standards must be implemented to allow for a more harmonious relationship between these shops and the environment. Third, both sellers and consumers think that taste, price, and freshness are important aspects of roadside agricultural product shops. However, while sellers and consumers both agree that the price is the most important factor, there is a discrepancy between these two groups regarding the satisfactory price level. The sellers do not agree that their products are being sold at the fair price. This can be interpreted as sellers believe that the prices are set too low. Because pricing is important aspect and also a very delicate issue, mid to long term consideration and study will be needed to improve roadside shops for agricultural products in the future.
For agricultural products, supply is irregular due to changes in meteorological conditions, and it has high price elasticity. For example, if the supply decreases by 10%, the price increases by 50%. Due to these fluctuations in the prices of agricultural products, the Korean government guarantees the safety of prices to producers through small merchants' auctions. However, when prices plummet due to overproduction, protection measures for producers are insufficient. Therefore, in this paper, we designed a business model that can be used in the electronic transaction system by predicting the price of agricultural products with an artificial intelligence algorithm. To this end, the trained model with the training pattern pairs and a predictive model was designed by applying ARIMA, SARIMA, RNN, and CNN. Finally, the agricultural product forecast price data was classified into short-term forecast and medium-term forecast and verified. As a result of verification, based on 2018 data, the actual price and predicted price showed an accuracy of 91.08%.
In this study, the local government proposes to improve agricultural products of the mall. Based on precedent studies, the variables that influence Customer Satisfaction are defined as; Product Quality, Delivery, Price. The result of study model verification is as below. Product Quality, Delivery and Price have positive influence on Customer Satisfaction. Price and Customer Satisfaction have positive influence on Repurchasing intention. Agricultural products through e-commerce transactions is increasing. But, the decreasing sales of professional Mall. Agricultural products have a variety of distribution channels. Because of the distribution system in a variety of price differences. People think that the most important factor is the price. Improvement is as follows. (1) To offer accurate product information, (2) Continuous content maintenance, (3) Conducted a variety of events, (4) To provide consumers with various benefits, (5) Offer a variety of product configurations, (6) Select the appropriate sales methods, (7) Provide ease of search.
Dried red peppers are a staple agricultural product used in Korean cuisine and as such, are an important aspect of agricultural producers' income. Correctly forecasting both their supply and demand situations and price is very important in terms of the producers' income and consumer price stability. The primary objective of this study was to compare the performance of time series forecasting models for dried red peppers in Korea. In this study, three models (an autoregressive model with exogenous variables [ARX], AR-exponential generalized autoregressive conditional heteroscedasticity [EGARCH], and ARX-EGARCH) are presented for forecasting the wholesale price of dried red peppers. As a result of the analysis, it was shown that the ARX model and ARX-EGARCH model, each of which adopt both the rolling window and the adding approach and use the agricultural cooperatives price as the exogenous variable, showed a better forecasting performance compared to the autoregressive model (AR)-EGARCH model. Based on the estimation methods and results, there was no significant difference in the accuracy of the estimation between the rolling window and adding approach. In the case of dried red peppers, there is limitation in building the price forecasting models with a market-structured approach. In this regard, estimating a forecasting model using only price data and identifying the forecast performance can be expected to complement the current pricing forecast model which relies on market shipments.
The purpose of this study is to analyze the effects of abolishing the low-pesticide agricultural product certification on environmentally friendly farming. A survey was conducted to quantitatively analyze farming practices and factors that change farming practice. It was found that only 17.0% of low-pesticide fruit farmers said that they will change their farming practice into organic or pesticide-free farming. With regard to the factors of farming practice change, binomial logistic regression model was applied for the analysis. In the analysis, it was found that farmers who grow the low-pesticide agricultural product are more likely to change their farming practice into organic or pesticide-free farming, as their expected price of organic or pesticide-free products is high, their area size is small, price premium of low-pesticide agricultural product is low, the frequency of their training is high. It is necessary to enhance the direct payment system to enlarge organic and nonpesticide acreage, and pest management techniques for fruits should be developed for low-pesticide fruit farmers to change their practice into organic and nonpesticide practice. Dissemination of cultivation manual, introduction of insurance to farmers, improvement of certificate system, and advertising and marketing of environment-friendly agricultural products are useful to develop environment-friendly agriculture.
This study aims to develop an integrated agricultural distribution network management system to improve the quality, profit, and decision-making efficiency of agricultural products. We adopt two key techniques: crop maturity detection based on the YOLOX target detection algorithm and market price prediction based on the Prophet model. By training the target detection model, it was possible to accurately identify crops of various maturity stages, thereby optimizing the shipment timing. At the same time, by collecting historical market price data and predicting prices using the Prophet model, we provided reliable price trend information to shipping decision makers. According to the results of the study, it was found that the performance of the model considering the holiday factor was significantly superior to that of the model that did not, proving that the effect of the holiday on the price was strong. The system provides strong tools and decision support to farmers and agricultural distribution managers, helping them make smart decisions during various seasons and holidays. In addition, it is possible to optimize the distribution network of agricultural products and improve the quality and profit of agricultural products.
Water is an essential resource for human survival. According to the OECD Environmental Outlook to 2050, rapid industrialization and a global population increase by approximately two billion will likely increase global water use by 55% in 2050. However, water depletion has been getting worse than before and has been happening more quickly, as Earth's water resources are limited. The present study proposes water management measures by using the virtual water theory which enables water consumption measurement and the confirmation and recognition of water scarcity problems, and will support the development of counter-measures. As a method for estimating the value of agricultural water, virtual water theory was used to calculate the amount of agricultural water input for domestic rice and to apply prices of agricultural water in the United States and China to Korean water prices. When the Chinese price was applied to Korean water prices, the value of agricultural water represented 0.3% of the Korean rice producer's price. When the US price was applied to Korean water prices, the value of agricultural water represented 1.6% of the domestic rice producer's price. The study exposes the percentage of the value of agricultural water in agricultural product prices, as well as how this scare resource may affect future prices. In the future, if there are water charges to effectively manage agricultural water, this study, which uses the virtual water theory, can be used as a preliminary research.
Agriculture is a primary industry that influenced by the weather or meterological factors more than other industry. Global warming and worldwide climate changes, and unusual weather phenomena are fatal in agricultural industry and human life. Therefore, many previous studies have been made to find the relationship between weather and the productivity of agriculture. Meterological factors also influence on the distribution of agricultural product. For example, price of agricultural product is determined in the market, and also influenced by the weather of the market. However, there is only a few study was made to find this link. The objective of this study is to investigate the effects of meterological factors on the distribution of agricultural products, focusing on the distribution of chinese cabbages. Chinese cabbage is a main ingredient of Kimchi, and basic essential vegetable in Korean dinner table. However, the production of chinese cabbages is influenced by weather and very fluctuating so that the variation of its price is so unstable. Therefore, both consumers and farmers do not feel comfortable at the unstable price of chinese cabbages. In this study, we analyze the real transaction data of chinese cabbage in wholesale markets and meterological factors depending on the variety and geography. We collect and analyze data of meterological factors such as temperatures, humidity, cloudiness, rainfall, snowfall, wind speed, insolation, sunshine duration in producing and consuming region of chinese cabbages. The result of this study shows that the meterological factors such as temperature and humidity significantly influence on the volume and price of chinese cabbage transaction in wholesale market. Especially, the weather of consuming region has greater correlation effects on transaction than that of producing region in all types of chinese cabbages. Among the whole agricultural lifecycle of chinese cabbages, 'seeding - harvest - shipment - wholesale', meterological factors such as temperature and rainfall in shipment and wholesale period are significantly correlated with transaction volume and price of crops. Based on the result of correlation analysis, we make a regression analysis to verify the meterological factors' effects on the volume and price of chines cabbage transaction in wholesale market. The results of stepwise regression analysis are shown in
and
. The type of chinese cabbages are categorized by 5 types, i.e. alpine, gimjang for winter, spring, summer, and winter crop, and all of the regression models are shown significant relationship. In addition, meterological factors in shipment and wholesale period are entered more in regression model than those in seeding and harvest period. This result implies that weather in consuming region is also important in the distribution of chinese cabbages. Based on the result of this study, we find several implications and recommendations for policy makers of agricultural product distribution. The goal of agricultural product distribution policy is to insure proper price and production cost for farmers and provide proper price and quality, and stable supply for consumers. Therefore, coping with the uncertainty of weather is very essential to make a fruitful effect of the policy. In reality, very big part of consumer price of chinese cabbage is made up of the margin of intermediaries, because they take the risk. In addition, policy makers make efforts for farmers to utilize AWIS (Agricultural Weather Information System). In order to do that, it should integrate the relevant information including distribution and marketing as well as production. Offering a consulting service to farmers about weather management is also expected to be a good option in agriculture and weather industry. Reflecting on the result of this study, the distribution authorities can offer the guideline for the timing and volume of harvest, and it is expected to contribute to the stable equilibrium of supply and demand of agricultural products.
Garlic and onion are staple agricultural products to Koreans and also are important with regard to agricultural producers' income. These products' acreage responses are highly correlated with each other. Therefore, it is necessary to test whether there is a cointegration relationship between garlic acreage and onion acreage when one tries to estimate the acreage response's function. Based upon the test result of cointegration, it is confirmed that there is no statistically significant cointegration relationship between garlic acreage and onion acreage. In this case, vector autoregressive model is preferred to vector error correction model. This study investigated the dynamic relationship between garlic and onion acreage responses using vector autoregressive (VAR) model. The estimated results of VAR acreage response models show that there is a statistically significant relationship between current and lagged acreage of more than one lag. Therefore, it is recommended that government should consider the long-run period's relationship of each product's acreage when it plans a policy for stabilizing the supply and demand of garlic and onion. For the price variables, garlic price only affects garlic acreage response while onion price affects not only onion acreage response but also garlic acreage response. This implies that the stabilizing policy for onion price could have bigger effects than that for garlic price stabilization.
We devised a grape variety model to estimate the impact of lowering the Shine Muscat quality level on the grape market. Shine Muscat has become a popular grape variety in Korea. Accordingly, the area devoted to the harvesting of Shine Muscat has increased dramatically since 2016. Our study examines how a reduction in the quality of Shine Muscat affects other grapes such as Campbell Early, giant peak, and Muscat Bailey A (MBA). The Armington model was used to impose consumer preferences and product differentiation assumptions. We found that a decrease in the consumer preference for Shine Muscat realized by lowering the quality of Shine Muscat largely reduces the price of this variety. Also, the prices of other grape varieties fell via a substitute effect. Moreover, if grape varieties were more differentiated, the reduction in the price of Shine Muscat would be greater, while the decreases in the prices of other grape varieties would be smaller. These results imply that farmers of Shine Muscat must continue with quality management efforts to avoid the negative effect of changing consumer behavior with regard to Shine Muscat against a reduction in its quality. Our model introduces a product differentiation model for the fruit market and helps policymakers and farmers understand the impact of changing market conditions in the fruit market.
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